Technical innovations in speech recognition technologies and information technologies have led to the development and widespread implementation of automated systems that support human-machine natural dialog interaction. For example, Interactive Voice Response (IVR) systems provide callers with automated customer service and self-help applications that can be accessed and controlled through speech dialog with the system over a telephone. These automated applications are designed with a goal of increasing customer satisfaction by providing fast access to information and services through automated customer service interactions, while decreasing operational costs associated with having to maintain a large pool of personnel to support live customer assistance.
Depending on a person's culturally-based latent (subconscious) tendencies and preferences with regard to automated and live customer service in the context of a given task, however, certain individuals may have a tendency to be uncooperative with automated systems and prefer live customer service. In this regard, automated systems are typically designed to provide automated customer service as the primary option, while providing human customer assistance as a secondary option when a caller manifests a tendency or preference for human assistance.
By way of example, automated customer service systems are typically designed to determine an individual's tendency to be uncooperative with automated assistance based on some external behaviors of the individual that are indicative of the individual's unwillingness to use (or cooperate with) the automated customer service system. For instance, when presented with a choice of options from a main menu, instead of picking or selecting from one of the options, uncooperative individuals will exhibit certain external behaviors, including but not limited to:
(a) pressing “zero” to reach a human Agent (in a touch-tone system);
(b) explicitly asking for a “customer service representative” or pressing “zero” (in a speech dialog system);
(c) staying silent so that the system (touch tone or speech) will time out and possibly transfer to an Agent; or
(d) uttering profanities or otherwise verbalizing the individual's disdain for automated customer service.
Although external individual behaviors such as those mentioned above are useful indicators that can provide some measure of an individual's preferences for human customer assistance over automated customer service, the use of such indicators to assess individual preference in customer service interactions does not provide any systematic cognitive-psychological basis for determining individual behavioral tendencies and preferences. Essentially, such external indicators are systematically and arbitrarily contrived, and cannot be applied as metrics in various ways for determining individual type from observable behavior, which leads to inconsistent (unverifiable) conclusions.
In view of the above, in the context of customer service interactions, there exists a significant challenge with regard to understanding and predicting an individual's behavioral tendencies and preferences for automated or human customer service assistance without relying on the more erratic features of conventional approaches which, in turn, rely on an individuals' external behavior as indices of an individual's tendency to be cooperative or uncooperative.